Machine Learning

How Behavox solutions work

Unsupervised learning

The system doesn't require initial training and comes with thoroughly tested out-of-the-box algorithms and scenarios

The machine learning methods have been designed and implemented to specifically deal with the problem of "unknown unknowns" (i.e. finding the right information without having to specify the exact criteria of the information sought in the search)

Learning from user actions

Learning is based on daily feedback provided to the system through normal course
of business (compliance workflow)

The system tunes itself to minimize both False Positive Rate (FPR) and False Negative Rate (FNR) on the basis of user actions

The system observes the content with which the user interacted and tunes itself to better discover such ‘quality’ content

The system processes user feedback to cases generated by the system to ensure it discovers similarly useful cases and eliminates any similar to those that were dismissed

Knowledge sharing between clients

Anonymized results of machine learning are aggregated from all clients and processed to improve algorithms and scenarios

Resulting optimizations have yielded an unprecedented increase in the system’s accuracy rate owing to the depth of the network knowledge base

Machine-extracted knowledge accumulates over time increasing the value over time for the existing clients and allowing new clients to instantly benefit from the historical process